
# 5 proven small business marketing strategies to generate more leads

Getting new leads through local business marketing is hard! You're already wearing multiple hats, and marketing usually falls to the owner. While you don't have the budget that large companies do for Google Ads or small business advertising, here's the good news - you don't need a massive budget or a marketing team to implement effective lead generation tips. Let me share some local marketing tactics that are working right now for businesses like yours.

## 1. Combine old school with new school (It really works)

Here's a success story that might surprise you: A roofing company in Iowa tried something interesting - they sent out 7,000 postcards to homeowners in storm-affected areas, but they didn't stop there. They also ran targeted Facebook ads to the same neighborhoods. The result? They landed 10 new roofing jobs worth $174,000 in revenue. That's a 3,297% return on their marketing spend.

**Why this works:** People might see your Facebook ad but scroll past. They might toss your postcard. But when they see your business in multiple places? That's when they start paying attention.

**Quick way to try this:**

- Pick a specific neighborhood or area
- Send out postcards with a clear offer (like a free inspection or consultation)
- Run Facebook ads targeting the same ZIP codes
- Make sure your message is the same everywhere
- Include a way to track where leads come from (unique phone numbers or offer codes)

## 2. Make Google Ads for small business work (without breaking the bank)

Here's a fact: 58% of small businesses are investing in search ads because they work. But you need to be smart about it. A small construction firm found success by focusing just on specific keywords like "home renovation [city name]" and "kitchen remodel near me" instead of trying to show up for everything.

**Quick way to try this:**

- Set up your Google Business Profile (it's free!)
- Ask happy customers to leave Google reviews
- Start with a small Google Ads budget ($300-500) targeting very specific local searches
- Create a simple landing page for each main service you offer

## 3. Best marketing strategies for small business: Turn your expertise into leads

A small manufacturing company tried something clever - they wrote detailed guides about their industry and offered them as free downloads on their website. They shared these on LinkedIn and through email. It worked because they weren't just selling; they were helping people solve problems.

**Quick way to try this:**

- Write down the top 3 questions customers always ask you
- Create short how-to guides or checklists about these topics
- Share them on your website in exchange for an email address
- Post parts of the content on LinkedIn (if you're B2B) or Facebook

## 4. Email marketing for small business (Because it still works better than you think)

Email marketing returns $36 for every $1 spent. That's not a typo. A family-run dental practice used email reminders and seasonal promotions to grow from $700k to $3.2 million in revenue. While you might not see those exact numbers, even small email campaigns can bring big results.

**Quick way to try this:**

- Start collecting emails (in person and on your website)
- Send a monthly update with useful info, not just sales pitches
- Use free tools like Mailchimp to automate your emails
- Always include a clear next step (book a consultation, request a quote, etc.)

## 5. Small business lead generation through customer advocacy

Word of mouth is still king, but you need to encourage it. A pool renovation company in Utah asked satisfied customers for before-and-after photos, then used these in their marketing. They brought in $250,000 in new projects from a campaign that cost just a few thousand dollars.

**Quick way to try this:**

- Take photos of your best work (before and after if possible)
- Ask happy customers for testimonials
- Share these stories on your website and social media
- Consider offering referral rewards to customers who send new business your way

## The bottom line

You don't need to do all of these at once. Pick one strategy that feels most doable for your business and start there. The key is to try something, measure the results, and adjust as needed. Remember that local business owner who started with just postcards and Facebook ads? They didn't know it would work until they tried it.

**Pro tip:** Whatever strategy you choose, track where your leads come from. A simple spreadsheet works fine - just note how each new customer found you. This will tell you what's working and what's worth your time and money.

Need more help? Consider joining your local business association, chamber of commerc or groups with other business owners. Other business owners are often happy to share what's working for them. Sometimes the best advice comes from people who've been right where you are.


How to effectively get new customers and grow your business.

5 proven ways to get more leads for your small business


The logistics industry keeps our world moving day in and day out. At $5.96 trillion, it is one of the largest sectors in the world. It's one of the industries that is poised to benefit greatly from developments in AI. We conducted research to understand the biggest opportunities for automation and how companies are leveraging AI today.

## Large opportunity for automation

According to [McKinsey](https://www.mckinsey.com/industries/metals-and-mining/our-insights/succeeding-in-the-ai-supply-chain-revolution), implementing AI has helped logistics companies improve costs by 15%, inventory levels by 35% and service levels by 65%. This comes as no surprise given the nature of the industry. The industry continues to trail other sectors when it comes to digital transformation. It is an operationally heavy sector with lots of rules, moving parts and regulations. This makes it ripe for disruption with AI.

Based on our research, we believe the following are the biggest opportunities for logistics companies and freight forwarders.

### Document processing

Logistics and freight companies deal with a lot of documents. The most common documents are the bill of lading, customs declaration forms, packing lists and invoices. There are many variations of these documents depending on the mode of transport and the origin / destination. These documents need to be produced, checked and then entered into several systems like a transport management system. AI can do all of this for teams. This reduces manual errors and frees up time for other, more valuable tasks.

### Better customer service

The freight and logistics industry is a highly competitive industry. Responding quickly and providing a high-level of customer service goes a long way in winning business. AI is helping companies by allowing them process quotes faster and respond to customers quickly. Some companies are going to the extent of leveraging AI to provide a 24/7 customer service experience for their customers. AI is able to answer many of the questions before these are passed on to the customer service team. This allows for a better customer experience and reduces costs for the business. Other players are leveraging AI to help their operations team find answers faster so that they can respond to customers more efficiently.

### Route optimisation and planning

Companies are using AI for route optimisation and planning. Some companies have been able to reduce fleet costs by up to 20% on fuel alone while significantly improving delivery efficiency. These systems analyze multiple variables simultaneously - including traffic patterns, delivery windows, vehicle capacity, driver schedules, and real-time road conditions - to determine the most efficient delivery routes. The technology goes beyond finding the shortest path; it creates intelligent delivery sequences that maximize the number of stops while minimizing resource usage. For logistics managers, this translates to tangible benefits: reduced fuel consumption, decreased vehicle wear and tear, improved driver productivity, and enhanced customer satisfaction through more accurate delivery times. Perhaps most importantly, route optimization software provides end-to-end visibility of all resource movement, enabling managers to track performance metrics in real-time and make data-driven decisions that further improve operational efficiency.

### Warehouse operations

Warehouse operations can benefit from AI particularly given the advancements we're seeing in vision based models. Dimensioning technology, combining high-quality cameras and precise scales, now automatically measures, weighs, and photographs cargo in seconds, replacing time-consuming manual processes that were prone to errors. These systems can reduce processing time by several minutes per item while improving accuracy in inventory counts. AI-driven inventory optimization goes beyond basic stock management, using predictive analytics to forecast demand patterns, optimize stock levels, and reduce both stockouts and overstock situations. The technology also revolutionizes picking and packing processes, with advanced algorithms optimizing picking routes and robotic systems working alongside human workers to enhance efficiency. This automation not only reduces labor costs but also provides real-time data integration with warehouse management systems, enabling better space utilization and more accurate billing. For warehouses handling high volumes, the return on investment is particularly rapid, with some facilities reporting the ability to reassign up to six forklift operators to other tasks after implementing automated systems.

### Financial operations

Freight and logistics companies deal with a lot of bills and invoices. Logistics companies transact over email and phone with parties, leaving the Finance team with a lot of paperwork to process. Many of these costs are also not finalised until after the shipment is complete. For example, if a shipment is waiting at a port for longer than it should have, the final payment will need to be adjusted. AI can help finance teams by reconciling data across documents, proactively flagging discrepancies and help process payments faster. Companies are applying this on the accounts payable side to pay vendors, and to receive payments faster from their own customers.

## Where do you start?

If you are a logistics or freight company, the AI landscape can be a little overwhelming right now. Customers often ask us where they should start. We recommend starting by identifying the biggest lever of change for your business. As the person on the ground, your team will be best placed to articulate what will move the needle the most. Pick the highest value item that you think can drive the business forward. Define a clear metric to measure impact. For example, if you believe winning business is a priority, choosing to reduce the time to quote may be a good way to get started. Once you do this, you can narrow the scope of possible solutions and then pick the one that best works for you.


Artificial intelligence in supply chain and logistics

AI-driven automation in the logistics and freight industry


Why did you send me a PDF? We've all been there.

The Portable Document Format (PDF) was invented by Adobe in the 90s. The goal was to make every file look the same, no matter what screen you viewed it on. Today, the PDF is a common file format because it allows the sender of the document to ensure that the file is read only. This makes it a common file format for sending documents to other people or businesses. PDFs are often used for invoices, bills, customer orders, logistics documents and more.

Teams often find themselves needing to convert PDFs to CSV so that they can compare data or enter it into a system. For example, an accounts payable team might want to convert all incoming vendor invoices into a CSV so that they can reconcile amounts against their own internal records (e.g. purchase orders). Here are other common use cases:

- Extracting data from freight documents
- Processing insurance claim documents
- Updating inventory based on catalogs and purchase orders
- Extracting data from bank statements

Here are 5 effective methods to convert PDF to CSV:

1. Manual Extraction: Copy and paste or manually transcribe data from PDF to a spreadsheet.
2. AI Assistants: Use tools like ChatGPT or Claude to extract and structure data from PDFs.
3. Web-based Converters: Utilize online tools such as SmallPDF, PDFGuru, or PDFTables for occasional conversions.
4. AI Document Processing: Employ advanced AI systems for high-volume, automated PDF data extraction.
5. Kili: Convert your PDFs to CSV files within minutes using our AI platform

Each method has its own advantages depending on your needs, volume of documents, and desired accuracy. We'll explore these options in detail below.

## Manually Converting PDF to CSV

For the sake of establishing a baseline, let's get the obvious method out of the way: extracting data manually. In most cases, users will have to manually transcribe each value from the PDF into an Excel file. If you're lucky, the PDF may be in a format that allows you to copy and paste data page by page into Excel. Even if this is the case, the output needs to be checked manually. You could easily end up with numbers that are missing a digit at the start or the end. This approach requires no additional tools but is time-consuming and error prone. Several businesses outsource the data extraction to other agencies.

## Using AI Tools to Transform PDF into CSV

AI assistants like ChatGPT or Claude can extract data from PDFs for you. Based on our experiments, ChatGPT is a superior option here because it will attempt to structure the data for you. Try a simple prompt like: "Extract xyz columns from this file and give it to me in a format that I can use to paste into Excel". The downsides of this approach are that it's still manual because you need to do one document at a time. In addition, we've found that accuracy is not very high. This method also doesn't do that well when you need to extract data from the table of a PDF. If you need to enter your data into another system like an ERP or accounting system, you will need to format your data before doing so. We recommend this method if you find yourself extracting data from a PDF occasionally and a little inaccuracy is not a problem.

## Web-based PDF to CSV Converters

There are many web based tools that allow you to upload a PDF and extract data from it. For example, SmallPDF, PDFGuru or PDFTables. These tools are a good option if you process PDFs only occasionally and are happy to do each one individually. When considering a tool, pay most attention to the accuracy of the output. For example, OCR based tools may face challenges with handwritten text, complex layouts, or poor-quality scans. Optical character recognition (OCR), as the name implies, attempts to recognise characters and not words. As a result, you frequently end up with instances where all but a few characters in a word match. This means your team needs to sift through those invoices manually anyway.

## AI Document Processing

AI document processing tools leverage a mix of large language models and vision models to extract data from PDFs. These systems can automatically identify and extract relevant information, process multiple documents simultaneously, and handle various layouts and formats. Some even offer validation and data cleaning features. They excel at processing large volumes of consistently formatted documents such as invoices, receipts, or contracts. Depending on the product, you may need to supply a sample of documents to "train" the product. If you process a large volume of documents and need to integrate the solution into your workflow, consider an AI document processing tool. Make sure to test the tool with your documents to verify the accuracy you need.

## Kili: Automated PDF to CSV Conversion

Kili is an AI document processing platform that helps businesses extract data with zero engineering effort. We require no pre-training and users can get started in minutes. Every document is extracted and stored in a [Board](/blog/announcing-boards).

To extract data from PDFs into a CSV file, follow these steps:

- Sign up for an account
- Set up a board. A board is a collection of documents (e.g. invoices) you want to extract data from. You can define the fields you want to extract and the format of these fields.
- Upload your documents
- Click 'Export' and download your CSV

At Kili, we use a combination of text and vision based AI models to extract data. We are able to extract data from a PDF that is more useful than OCR. Every single entry is validated according to the format you request. In addition to the above, we can help you process documents via email and provide your team with a simple interface to update data when it's missing or incorrect. Get in touch with our team for a personalised demo of our product.

## To close

PDFs are a common type of unstructured document format and teams frequently find themselves needing to extract data from PDFs to a CSV. You can extract data by doing it manually, using ChatGPT, using web-based tools or an AI document processing tool like Kili. If your team processes a high volume of documents and the accuracy of extraction is important, we recommend a document processing tool like Kili.


Learn how to convert PDF to CSV with 5 effective methods, from manual extraction to AI-powered tools. Discover the best approach for your needs, whether you're handling occasional files or high-volume document processing.

How to Convert PDF to CSV: 5 Effective Methods


Today, we're excited to announce Boards, a new way to process documents by leveraging AI.

80% of the data every business deals with is in the form of emails, PDF, pictures, documents or some other unstructured form. Boards transform this data, automating extraction and streamlining operations across departments.

## Why we're building Boards

With the advent of AI, we believe software should mould itself to your business rather than your business moulding to the software. Truly flexible software today comes in the form of either Excel, Google Sheets, or an expensive ERP solution. We've learnt from customers that graduating from a Google Sheet to an ERP is a painful process. ERPs are inflexible, costly to implement and tough to maintain. Boards are our answer to this problem.

## Flexible document processing

Boards offer flexible, intelligent document processing. A board is a set of documents that you want to extract data from. Set up custom fields to capture critical information from any document type within minutes. Simply send us or upload the documents, and we'll extract everything you need. As your business changes, add fields and we'll automatically extract them for you.

## Automating data entry with AI

Business teams waste countless hours on manual data entry from documents, PDFs and emails. Boards eliminate this tedious task through automated document processing processing and intelligent data extraction. Data is always validated and consistent.

Users can upload files, email them or leverage our API. Our AI-powered system significantly reduces processing time and improves accuracy for various business workflows.

## Automations in the background

Going forward, we will be adding automations to boards. For example, we can automatically route documents to the right person based on the information in the document. We can also automatically check for errors in the document and flag them to the right person. We imagine having an AI agent for each type of workflow that a customer needs to do (e.g. accounts payable).

## Use cases

Here are some workflows boards can assist with:

- Streamlining accounts payable workflows
- Processing logistics and customs documents
- Extracting data from insurance claims
- Enhancing sales order processing efficiency
- Centralizing contract management with intelligent data extraction

## Demo

Check out a demo of how Kili can do this for you [here](https://www.loom.com/share/8893fd608ab842c39298db7a93a640f7).


Leverage generative AI to automate document processing and streamline business workflows

Announcing Boards: the new way to store documents


We're excited to announce that Kili is now open to everyone. Kili helps you automate repetitive tasks. We wanted to write a short note explaining our vision and why we're excited about it.

Large language models (LLMs) will help us automate many of the tasks we do today. LLMs provide intelligence on the fly, and we believe we are only scratching the surface of what's possible with this technology.

Importantly, we want this technology to be available to everyone. Most of the work we do today is tedious and repetitive. Teams rely on their engineering counterparts to automate processes, or rely on software that is available off the shelf. With the power of LLMs, we believe it's now possible to build an automation within minutes. This means software can be customised and built for what you need rather than the other way around - you having to mould to what the software does under the hood.

To achieve our vision, we believe the user interface is critical. We've had no-code and low-code apps for many years. They've grown in popularity but are limited either by inflexibility, their complexity or both. Kili is our attempt to build the next version of this using LLMs from the ground up.

We believe chat interfaces are great for their simplicity. They do not work for complex tasks. On the other hand, most people think visually. Visual node-based user interfaces attempt to solve for this but are typically complex with many elements and buttons. Our user interface combines the best of both worlds. It allows users to review their task from a visual point of view, and leverage our AI assistant to build or manage their automation.

Our assistant and the visual canvas share the same information. This means the assistant can take actions for you that update the canvas. The assistant can zoom in and answer a question about a specific step, or zoom out and figure out what you should do next to achieve the goal of your automation.

Sign up for a free account [here](https://app.kili.so/auth/signup) and check out the demo video [here](). We're excited to see what you build!


Why we're building Kili


Accounts payable departments play a crucial role in managing supplier payments. However, the process can be time-consuming and error-prone, especially for companies dealing with a high volume of invoices. Key challenges include:

- Time-consuming data entry
- Accuracy issues leading to over or underpayments
- Fraud prevention concerns
- Difficulty in scaling operations

Thanks to the power of AI and intelligent document processing, companies can now automate significant portions of the invoice process. This allows accounts payable teams to process more invoices efficiently and focus on those that truly matter. Let's break down the invoice processing steps and see how AI can streamline each one:

## 1. Extract information from PDFs and Emails

Most invoices arrive via email, with important information contained in PDF attachments and sometimes in the email body itself. The first step is extracting data from both sources. While traditional OCR has been effective, the advent of large language models has significantly improved this process, especially when dealing with complex table structures in PDFs.

## 2. Validate information and perform 3-way matching

Once data is extracted from the invoice, it needs validation. Every business has unique rules for validating invoices, and any automation tool should accommodate these custom requirements. The validation process includes:

1. Checking for the presence of all required information (e.g., VAT numbers)
2. Matching the invoice against purchase orders (POs), receipts, or other internal records (3-way matching)

By leveraging AI, this matching process can be automated, allowing your team to focus on invoices that are either high-value, unmatched, or both.

## 3. Approve invoices with customized workflows

Most businesses have specific approval chains for invoices, typically routing them based on supplier name, amount, or both. It's crucial that your invoice processing software allows for customization of these rules and flags instances where the approval chain is broken due to organizational changes.

## 4. Integrate with Your ERP or Accounting Software

One of the most time-consuming aspects of invoice processing is inputting data into your ERP or accounting software. Each ERP system requires information in a specific format, while incoming invoices come in various formats. The best invoice processing software will:

1. Automatically transform extracted information into the required format
2. Push data directly to your ERP system

With the power of LLMs and AI, this process can be highly automated, reducing errors and saving time.

## 5. Measure Success and Optimize

To ensure your automated invoice processing is effective, track these key metrics:

1. Processing time (from receipt to payment)
2. Error rate (duplicate payments, data errors, payment errors)
3. Average approval time
4. Supplier satisfaction

## Automate Invoice Processing with Kili: Your AI-Powered Solution

Kili provides an out-of-the-box solution to automate invoices received via email. Our AI-powered document processing platform:

1. No Engineering Effort Required: Get started in minutes with our user-friendly platform.
2. Flexible Input Options: Process documents via our UI, API, or email.
3. Comprehensive Data Extraction: Extract data from PDFs, images, and any other document type.
4. Easy Integration: Connect seamlessly with your existing business systems.
5. Customizable Workflows: Tailor the process to your specific needs.

Get in touch with us to streamline your accounts payable process.


Streamline your accounts payable process with AI-powered invoice automation. Learn how to extract data from PDFs, validate information, and integrate with ERPs to save time and reduce errors.

Automate invoice processing: streamline your accounts payable workflow


Every job involves some amount of repetitive work. The account executive who needs to enter information into their CRM, or the HR executive who needs to answer the same question about paid time off.

If these tasks are repetitive, why hasn't software delivered on the promise of automation? Usually, there are two reasons: first, the task may be ever so slightly different when you choose to do it. Second, the effort of automating the task may have exceeded the value of doing so.

## Thinking on the fly

Large language models (LLMs) allow us to address both of these issues, unlocking automation like never before. It is now possible to build automations that are fluid. Consider the sales executive who needs to keep their CRM up to date. The information required to update the CRM lives in calls, emails and any notes they've taken. If they need to format this information for the CRM, they may as well just do it via the Salesforce (or whatever CRM they use) user interface.

On the other hand, if the update happened automatically by plugging into these resources, it would save the Account Executive precious time. Time that can be spent following up with leads and closing more deals. Large language models make this possible because they provide intelligence on the fly. The LLM can summarise the content and format it for the CRM. In the best case scenario, the AE needs to do nothing because information moves seamlessly into the CRM.

## Human in the loop

In some cases, we will find that AI needs to work in partnership with a human. The best example of this is the financial operations function. Every business needs to receive invoices, check them and pay vendors. This is typically handled by an accounts payable function.

Today, most businesses have software that helps with this but the automation is incomplete. This is because every business has it's unique process for handling invoices, and because every invoice looks different. Traditional automation tools like robotic process automation have low success rates because of this variance in the process.

LLMs address this shortcoming because they allow us to process information that may not always follow the same structure, like invoices. They significantly improve accuracy and reduce fraud. Even with LLMs, you require a human in the loop to avoid any chance of a mistake. The difference though is that it allows your team to handle more invoices whilst simultaneously improving reliability.

This human, AI collaboration also allows your team to work on the most pressing issues. For example, an invoice that looks fraudulent or resolving an issue that may have sent the funds to the wrong bank account.

## Employees managing digital workers

At Kili, we believe AI will enable every employee to 10x their output. We believe they will do so by managing digital workers that complete repetitive tasks for them. Instead of spending time getting context from different systems, employees will be able to spend time on what decision to make.

We believe in a world where AI quietly does work for your team in the background, and only reaches out to them when they need to make a decision. We're excited for this future and are building for it.

Join our closed beta if you're interested in leveraging this capability for your business.


Explore how AI-powered solutions and generative AI applications for document extraction can revolutionize your workflow. Learn about delegating repetitive tasks and increasing productivity with intelligent automation.

Blog

5 proven ways to get more leads for your small business

AI-driven automation in the logistics and freight industry

How to Convert PDF to CSV: 5 Effective Methods

Automate invoice processing: streamline your accounts payable workflow

Delegate your repetitive tasks